真实网络中的可观测性变迁
Observability transition in real networks
摘要：
我们考虑了任意拓扑网络的可观测性模型。我们引入了一个系统的耦合非线性方程，有效的局部树型的ananonymous下，描述的最大的可观察集群的大小作为一个函数的分数的直接可观察的节点存在于网络中。我们对95个真实世界的图进行了系统的分析，并将我们的理论预测与可观测性模型的数值模拟进行了比较。我们的方法在大多数情况下提供了几乎完美的预测，即使是对于具有非常大的聚类系数值的网络。我们的理论的潜在应用包括开发用于实时监控社交网络和监控技术网络的高效和可扩展的算法。
英文摘要：
We consider the observability model in networks with arbitrary topologies. We introduce a system of coupled nonlinear equations, valid under the locally tree-like ansatz, to describe the size of the largest observable cluster as a function of the fraction of directly observable nodes present in the network. We perform a systematic analysis on 95 real-world graphs and compare our theoretical predictions with numerical simulations of the observability model. Our method provides almost perfect predictions in the majority of the cases, even for networks with very large values of the clustering coefficient. Potential applications of our theory include the development of efficient and scalable algorithms for real-time surveillance of social networks, and monitoring of technological networks.
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